What does it truly take to be a leader in the fields of statistics, data science, or programming?
Is it just about mastering complex skills and techniques?
In this eye-opening episode, I challenge the conventional view of leadership.
Together with Paolo, We kick off by revisiting the basics of linear models and why they form such a crucial foundation in data analysis. From there, we delve into the fascinating history of linear mixed effects models, tracing their development back to the early ’80s with Lerder Rubin’s influential work.
I am eager to navigate the “4+1 phases of learning” with you today. This topic, central to our leadership course, particularly targets supervisors but resonates with everyone in a professional setting.
In today’s episode, Benjamin and I dive into the critical issue of retaining key team members, especially now that he has earned his promotion to Global Head of Biostatistics within PBS at CYTEL.
President at Mediana LLC Understand and master multiplicity in practical situationswith Alex Dmitrienko
Visualization designer, author, teacher, and consultant Alberto Cairo is a journalist and designer, and the Knight Chair in Visual Journalism at the School of Communication of the University of Miami (UM). He is also the director of the visualization program at UM’s Center for Computational Science. He has been head of information graphics at media … Weiterlesen …
Statistical Research Fellow at UCB Helping Statisticians having a bigger rolewith Andy Grieve
Have you ever wondered about the complexities that arise within pharmaceutical companies due to the division between global and local operations?
Why do these realms often operate with such distinct perspectives, and how do they impact our mission to deliver effective healthcare solutions globally?
Expert Statistical Scientist at Roche Managing Hype in Statisticswith Kaspar Rufibach
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